Making Enterprises Resilient While Accelerating Secure Cloud Migration

My previous blog, “Why Move Data to the Cloud Despite Various Data Privacy and Security Risks,” covered business and technical drivers that led enterprises to transition to the cloud for a better data analytics experience. This blog will explore how an enterprise can become resilient in its cloud data analytics journey by accelerating secure cloud migration.

Making enterprises resilient while accelerating secure cloud migrationSecure data migration to the cloud remains the primary concern to be addressed by enterprises. Irrespective of the cloud deployment model, the data security remains with the enterprise as per the shared responsibility model. Under this model, cloud providers will ensure that the hardware and software services are secure. Enterprises should perform diligent risk assessments and identify the risks that may remain unaddressed with the adoption of data analytics serverless services provided by cloud data warehouses (CDW) and cloud services providers (CSP).

Inherent CDWs and CSPs native security controls protect data at rest and in motion. These security controls are referred to as transparent data encryption or dynamic data masking. Once data is in the cloud, it needs to be accessed by applications and various stakeholders for business operations. Ensuring that data remains protected and yet useable by cloud applications and services in its protected form should be the baseline for any or every cloud data migration strategy.

A Data Privacy and Protection Perspective

From a data privacy and protection perspective, what always works well is first to identify sensitive data and then apply data-centric security, which persistently protects data throughout its lifecycle. This approach enables enterprises to: 

  • Consistently protect data regardless of where it is stored or processed – Reduce the risk of cloud-based data breaches and insider attacks in a shared environment. Therefore, neutralizing data breach impacts by rendering data unusable by attackers.
  • Scale and be agile – Remain in control of your data security while you run analytics at scale in cloud data warehouse systems.
  • Simplify regulatory compliance in cloud-based analytics, applications, and business processes – Remove the requirement for breach notification of affected consumers under regulations such as the GDPR, where personal data has been protected.
  • Accelerate secure cloud migration – Accelerate your cloud migration with a proven data-centric security to safely deploy applications, data, and workloads. Manage data protection persistently across hybrid IT, Infrastructure as a Service (IaaS), Software as a Service (SaaS), or Platform as a Service (PaaS), with platform-agnostic solutions with greater flexibility to scale in multi-cloud or hybrid ecosystems.

Voltage SecureData can help on your journey to secure cloud analytics for the following reasons:

  1. Voltage SecureData protects sensitive data persistently across multi-cloud, hybrid, and on-premises environments. It embeds data-centric security across hybrid IT and, by reducing the risk to sensitive data, accelerates the safe migration to cloud environments.
  2. Voltage SecureData Cloud provides security servers and clients that enable applications, data, and data stores to interoperate with on-premises and in-cloud services to provide end-to-end protection across the data lifecycle.
  3. Voltage data protection preserves data usability post tokenization. The tokenization technologies in Voltage SecureData provide flexible implementation and protection for a virtually unlimited number of structured data types in any language and region, with proven performance and scalability. Voltage Format-Preserving Encryption (FPE), Format-Preserving Hash (FPH), and Secure Stateless Tokenization (SST) enable enterprises to de-identify sensitive information in ways that neutralize the effects of a data breach. Still, they permit continued use of the data in its protected state in applications and analytics platforms.
  4. Data Pseudonymization with Voltage FPE, a mode of the Advanced Encryption Standard (AES), is a fundamental innovation which enables SecureData Cloud to provide high-strength, robust data encryption while maintaining flexibility for use. An implementation of the FF1 method as presented in NIST SP 800-38G3, Voltage FPE is a cryptographic standard that provides the pseudonymization necessary to enable compliance with data privacy regulations at data field and sub-field levels. While simultaneously allowing the organizations to run business processes and analytics on protected data sets.
  5. Voltage Secure Stateless Tokenization (SST) is an advanced, patented data security solution that helps protect payment card data on-premises or in the cloud. Voltage SST eliminates the token database and removes the need for the cardholder or other sensitive data storage, enabling a vast reduction in the scope of a PCI-DSS compliance audit, for example. Using a set of static, pre-generated tables to consistently produce a unique, random token for each data value, such as a Primary Account Number (PAN), optimizes the tokenization process's speed, scalability, security, and manageability.
  6. Voltage Stateless Key Management is the cornerstone of Voltage's simplicity and scalability. Keys are derived dynamically as required, with no key database to store, protect, backup, or integrate with traditional key management solutions. Enterprises do not need to manage keys, certificates, or databases, eliminating the hardware, software, and IT and personnel processes and costs required to continuously protect key databases on-premises, in off-site back-ups, or even in the cloud.

The last blog of the series will examine how our industry-leading Voltage data protection solution offers various data-protection techniques across cloud platforms: stay tuned!

 

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